Dr. Dongbin Qian Qian | Materials Science| Best Researcher Award

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Dr. Dongbin Qian Qian | Materials Science| Best Researcher Award

Dongbin Qian Qian, Institute of Modern Physics, Chinese Academy of Sciences, China

Dr. Qian Dongbin is a renowned professor at the Institute of Modern Physics, Chinese Academy of Sciences, specializing in laser-induced breakdown spectroscopy (LIBS) for analyzing trace elements in loose powders. He has an extensive background in atomic and molecular physics, holding a Ph.D. from the same institute. His research interests focus on the development of LIBS technologies and their application in various fields such as material science, environmental monitoring, and energy. He has contributed significantly to both academic research and technology development. His research is marked by innovation, with collaborations across international research institutions. 🌍🔬✨

Professional Profile:

SCOPUS

🎓 Education & Experience

QIAN Dongbin obtained his Ph.D. (2007) in Atomic and Molecular Physics from the Institute of Modern Physics (IMP), CAS, after completing his Bachelor’s (2002) in Theoretical Physics at Qufu Normal University. 📘 He began his academic career as an Assistant Professor at IMP in 2007, rising to Associate Professor in 2009 and Full Professor in 2017. 👨‍🏫 His academic journey reflects a strong commitment to applied spectroscopy, particularly in plasma analysis for granular and soft materials. 🧬 Throughout his career, he has contributed extensively to national projects and international collaborations. 🌐

🌍 Professional Development

Prof. Qian has cultivated international expertise through repeated research visits to CNRS-ILM, University Lyon 1, between 2009–2016. ✈️ His role as a Visiting Researcher enhanced collaborations in laser-plasma interactions. He received the CAS Youth Innovation Promotion Association Fellowship (2011–2014), reinforcing his leadership among emerging scientists. 🌟 His excellence was recognized with the Young Scientists and Talents Award (2014). 🏆 Through national and international projects, Prof. Qian continues to contribute to cutting-edge LIBS technology, combining experimental physics with data-driven techniques like deep learning and AI-assisted spectroscopy. 🤖

⚗️ Research Focus 

Prof. Qian’s research lies at the intersection of Applied Physics, Spectroscopy, and Materials Science. 🌡️ His work with laser-induced breakdown spectroscopy (LIBS) targets trace element detection in powders and the characterization of soft materials. He integrates machine learning models, such as transformers and CNNs, with spectroscopic data for enhanced precision. 🧠📊 His studies extend to grain size analysis, surface flatness inspection, and plasma behavior in microgranular systems, making significant strides in analytical atomic spectroscopy and AI-powered material diagnostics. 🧪 His interdisciplinary focus supports advancements in both industrial applications and fundamental plasma research. 🔬

🏅 Awards & Honors

Prof. Qian has received numerous accolades, including the Young Scientists and Talents Award (2014) from the Institute of Modern Physics. 🎖️ He was also selected for the prestigious CAS Youth Innovation Promotion Association Fellowship (2011–2014). 🧠 His international recognition is reflected in multiple Visiting Researcher appointments at CNRS-ILM, France. 🌍 He has successfully led major National Natural Science Foundation of China (NSFC) projects and CAS-funded initiatives. 📑 His leadership and innovation have solidified his reputation as a pioneer in LIBS development, machine learning integration, and atomic spectroscopy research. 🚀

Publication Top Notes:

1. Transformer-based deep learning models for quantification of La, Ce, and Nd in rare earth ores using laser-induced breakdown spectroscopy

Authors: Jiaxing Yang, Shijie Li, Zhao Zhang, Xiaoliang Liu, Zuoye Liu
Journal: Talanta, 2025
Citations: 0
Summary:
This study introduces a transformer-based deep learning model to quantify lanthanum (La), cerium (Ce), and neodymium (Nd) in rare earth ores using laser-induced breakdown spectroscopy (LIBS). The approach enhances accuracy over traditional regression methods by capturing complex spectral features and nonlinearities. The model shows promise for rapid and non-destructive elemental analysis in geological and mining applications.

2. Detection of cesium in salt-lake brine using laser-induced breakdown spectroscopy combined with a convolutional neural network

Authors: Xiangyu Shi, Shuhang Gong, Qiang Zeng, Xinwen Ma, Dongbin Qian
Journal: Journal of Analytical Atomic Spectrometry, 2025
Citations: 0
Summary:
The paper demonstrates the detection of cesium (Cs) in salt-lake brine using LIBS enhanced with convolutional neural networks (CNNs). The CNN approach effectively handles high-noise spectral data, improving detection sensitivity and accuracy. The work supports the application of AI-assisted LIBS in environmental and resource monitoring of aqueous solutions.

3. Packing thickness dependent plasma emission induced by laser ablating thin-layer microgranular materials

Authors: Kou Zhao, Qiang Zeng, Yaju Li, Lei Yang, Xinwen Ma
Journal: Journal of Analytical Atomic Spectrometry, 2024
Citations: 0
Summary:
This study explores how the thickness of microgranular material layers affects plasma emission in LIBS. It provides insights into ablation dynamics and signal variations, highlighting the importance of sample preparation in quantitative LIBS analysis. The findings contribute to standardizing LIBS for layered or coated materials.

4. Laser-induced breakdown spectroscopy as a method for millimeter-scale inspection of surface flatness

Authors: Jinrui Ye, Yaju Li, Zhao Zhang, Lei Yang, Xinwen Ma
Journal: Plasma Science and Technology, 2024
Citations: 0
Summary:
This paper proposes a novel use of LIBS for assessing surface flatness at millimeter resolution. The technique exploits emission intensity variations due to laser focus offset, correlating them with surface deviations. It provides a non-contact alternative to mechanical profilometry for industrial applications.

5. Estimating the grain size of microgranular material using laser-induced breakdown spectroscopy combined with machine learning algorithms

Authors: Zhao Zhang, Yaju Li, Guanghui Yang, Shaofeng Zhang, Xinwen Ma
Journal: Plasma Science and Technology, 2024
Citations: 0
Summary:
The authors develop a LIBS-machine learning framework to estimate grain size in microgranular materials. By training algorithms on spectral data, they achieve high accuracy in distinguishing particle size distributions. This method offers a fast, non-invasive alternative to traditional sieving or microscopy.

Conclusion

Dr. Qian Dongbin’s blend of innovative research, global collaboration, and leadership in the scientific community makes him an ideal candidate for the Best Researcher Award. His work significantly advances both the technology of LIBS and its applications in environmental and material science, providing tangible benefits to society. His ongoing contributions to scientific excellence and research leadership clearly establish him as an exemplary figure in the field. 🌟🔬

 

Assoc. Prof. Dr | Quantum spin sensing and regulation and sensing optimization | Best Researcher Award

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 Dr. Yifan Zhao |  Quantum spin sensing and regulation and sensing optimization | Best Researcher Award

associate professor at Xi’an Jiaotong University,China

Yifan Zhao is an Associate Professor and PhD supervisor at the School of Instrument Science and Technology, Xi’an Jiaotong University. He is a member of the China Micro-Nano Technology Society and an expert committee member of the Functional Materials and Devices Committee of the Scientists’ Think Tank of the New Materials Development Alliance. In his academic career, Zhao has demonstrated leadership as a guest editor and young editor for prominent journals like Nanomaterials and Exploration. His primary research interests lie in precision manufacturing, quantum spin sensing, flexible thin film electronics, and measurement traceability.

Publication Profile

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Early Academic Pursuits 📚

Yifan Zhao’s academic journey is a testament to his dedication and passion for research in precision manufacturing and sensing technologies. He began his education at Xi’an Jiaotong University, where he excelled in the field of Instrument Science and Technology, eventually earning a position as an associate professor. His early interest in high-performance sensing technology and its applications in precision manufacturing laid the foundation for his future research focus. His pursuit of knowledge in quantum spin sensing and MEMS processing has positioned him as a leading figure in these cutting-edge areas. Zhao’s journey exemplifies the importance of a strong academic base, which has shaped his innovative contributions to technology and research.

Professional Endeavors and Contributions 🔧

Dr. Zhao has established himself as a key player in China’s precision manufacturing sector. As a professor at Xi’an Jiaotong University, he is deeply involved in research on quantum spin sensing, intelligent flexible thin film electronic sensing, and precise structure manufacturing. These technologies have significant implications for fields such as MEMS (Microelectromechanical Systems) processing, which is critical for the development of high-performance sensors used in various industries. Zhao’s professional endeavors extend beyond teaching and research—he actively contributes to the advancement of the field through leadership roles. He is a member of the China Micro-Nano Technology Society and serves on the expert committee of the Functional Materials and Devices Committee, demonstrating his influence in scientific communities. He is also a guest editor for the Nanomaterials and Exploration journals, where he plays a role in shaping research dissemination.

Research Focus: Precision Manufacturing and Sensing Applications 🔍

Yifan Zhao’s research primarily revolves around the integration of advanced sensing technologies and precision manufacturing techniques. His focus on quantum spin sensing and regulation is pushing the boundaries of scientific understanding in quantum technologies, which are integral to the next generation of highly sensitive measurement devices. Zhao also investigates intelligent flexible thin film electronics—materials and devices that are adaptable and have immense potential in wearable and flexible electronics. Furthermore, his work on precise structure manufacturing and measurement traceability addresses the challenges of producing and verifying the accuracy of micro and nanoscale devices. His work is not only highly theoretical but also has practical applications, as evidenced by the numerous patents he has filed, including over 10 domestic patents and one US patent. These advancements have profound implications for the future of sensor technology and its real-world applications in industries like healthcare, manufacturing, and environmental monitoring.

Accolades and Recognition 🏆

Dr. Zhao’s innovative contributions to science and technology have earned him significant recognition. He has published 23 SCI-indexed papers since 2017, many of which are in prestigious journals such as Advanced Materials, Nano Today, and Advanced Science. These publications have garnered attention from researchers worldwide, solidifying his reputation as a leading figure in his field. Zhao’s work has been cited extensively, contributing to the advancement of technologies in quantum sensing, flexible electronics, and MEMS. In addition to his research, Zhao has been a prominent figure in securing funding for scientific initiatives, having led over 10 national key research and development projects, including projects from the National Natural Science Foundation of China. His accolades extend beyond publications, reflecting his substantial impact on both academia and industry.

Impact and Influence 🌍

Yifan Zhao’s impact extends far beyond his research publications. His pioneering work in quantum sensing and advanced manufacturing technologies has placed him at the forefront of scientific and technological advancements. His influence is particularly notable in China’s development of high-performance sensing technology, where his research directly addresses the country’s demand for cutting-edge solutions in precision manufacturing. Zhao’s work on flexible electronics and MEMS technologies is contributing to the global progress of nanotechnology and quantum sciences. Furthermore, his leadership in national and international scientific communities ensures that his research remains integral to the broader scientific dialogue. As a mentor to PhD students and young researchers, Zhao is helping cultivate the next generation of leaders in his field, ensuring his legacy and influence will continue for years to come.

Legacy and Future Contributions 🔮

Yifan Zhao’s career trajectory suggests a future rich in continued innovation and discovery. His work in quantum spin sensing, MEMS, and flexible electronics has already reshaped current technologies, and as the demand for these technologies grows, his research will likely play an even more pivotal role. Zhao’s ongoing contributions to the development of precise manufacturing methods and his commitment to improving the traceability of measurement devices indicate that his influence will continue to grow, especially in industries where precision is paramount. As he continues to lead high-impact projects and mentor emerging researchers, Dr. Zhao’s legacy will undoubtedly endure, marking him as a key figure in the advancement of both scientific knowledge and practical applications in the fields of sensing and manufacturing.

Publication Top Notes

  1. Wang, S., Wang, C., Zhao, Y., Zhang, Y., Zhang, Y., Xu, X., Lin, Q., Yao, K., Wang, Y., Han, F., Sun, Y., Jiang, Z.. Microsystems & Nanoengineering, 10(1), 24. (2024) 📅 (IF=7.7)
  2. Wang, C., Du, Y., Zhao, Y., He, Z., Wang, S., Zhang, Y., Jiang, Y., Du, Y., Wu, J., Jiang, Z., Liu, M.. Nanomaterials, 13(24), 3158. (2024) 📅 (IF=5.3)
  3. He, Z., Zhao, Y., Du, Y., Zhao, M., Jiang, Y., Liu, M., Zhou, Z.. Frontiers of Physics, 19(4), 43206. (2024) 📅 (IF=6.5)
  4. Zhao, M., Zhao, Y., Li, Y., Dong, G., He, Z., Du, Y., Jiang, Y., Wu, S., Wang, C., Zhao, L., Jiang, Z., Liu, M.. Advanced Materials, 35, 2303810. (2023) 📅 (IF=29.4)
  5. Zhao, M., Wang, L., Zhao, Y., Du, Y., He, Z., Chen, K., Luo, Z., Yan, W., Li, Q., Wang, C., Jiang, Z., Liu, M.. Small, 19, 2301955. (2023) 📅 (IF=15.6)
  6. Du, Y., Zhao, Y., Wang, L., Wu, K.Y., Wang, C., Zhao, L., Jiang, Z., Liu, M., Zhou, Z.. Small, 2302884. (2023) 📅 (IF=15.6)
  7. Zhang, Y., Wang, Y., Wang, C., Zhao, Y., Jing, W., Wang, S., Zhang, Y., Xu, X., Zhang, F., Yu, K., Lin, Q., Mao, Q., Han, F., Tian, B., Zhou, Z., Ren, W., Liu, M., Jiang, Z.. Chemical Engineering Journal, 454. 139990. (2023) 📅 (IF=16.7)
  8. Li, C., Li, Y., Zhao, Y., Du, Y., Zhao, M., Peng, W., Wu, Y., Liu, M., Zhou, Z.. Advanced Functional Materials, 32(16), 2111652. (2022) 📅 (IF=19.9)
  9. Zhao, Y., Du, Y., Wang, L., Chen, K., Luo, Z., Yan, W., Li, Q., Jiang, Z., Liu, M., Zhou, Z.. Nano Today, 46, 101605. (2022) 📅 (IF=18.9)
  10. Peng, W., Wang, L., Li, Y., Du, Y., He, Z., Wang, C., Zhao, Y., Zhuang, J., Zhou, Z., Liu, M.. Journal of Alloys and Compounds, 910, 164903. (2022) 📅 (IF=6.63)
  11. Du, Y., Wang, S., Wang, L., Jin, S., Zhao, Y., Min, T., Jiang, Z., Zhou, Z., Liu, M.. Nano Research, 15(3), 2626-2633. (2022) 📅 (IF=10.2)
  12. Peng, W., Wang, L., Li, Y., Du, Y., He, Z., Wang, C., Zhao, Y., Jiang, Z., Zhou, Z., Liu, M.. Advanced Materials Interfaces, 9, 2200007. (2022) 📅 (IF=6.38)
  13. Zhang, Y., Wang, C., Jing, W., Wang, S., Zhang, Y., Zhang, L., Zhang, N., Wang, Y., Zhao, Y., Lin, Q., Jiang, Z.. Micromachines, 13(7), 995. (2022) 📅 (IF=3.52)
  14. Zhao, Y., Zhao, M., Tian, B., Jiang, Z., Wang, Y., Liu, M., Zhou, Z.. ACS Applied Materials & Interfaces, 13(1), 2018-2024. (2021) 📅 (IF=10.3)
  15. Zhao, Y., Zhao, S., Wang, L., Wang, S., Du, Y., Zhao, Y., Jin, S., Min, T., Tian, B., Jiang, Z., Zhou, Z., Liu, M.. Nanoscale, 13(1), 272-279. (2021) 📅 (IF=8.3)
  16. Zhao, S., Zhao, Y., Tian, B., Liu, J., Jin, S., Jiang, Z., Zhou, Z., Liu, M.. ACS Applied Materials & Interfaces, 12(37), 41999-42006. (2020) 📅 (IF=10.3)
  17. Zhao, Y., Zhao, S., Wang, L., Zhou, Z., Liu, J., Min, T., Peng, B., Hu, Z., Jin, S., Liu, M.. Advanced Science, 6(24), 1901994. (2019) 📅 (IF=17.5)
  18. Zhao, Y., Wang, G., Wang, Y., Xiao, T., Abdullah Adil, M., Lu, G., Zhang, J., Wei, Z.. Solar RRL, 3(3), 1800333. (2019) 📅 (IF=9.17)
  19. Zhang, J., Zhao, Y., Fang, J., Xia, B., Wang, G., Wang, Z., Zhang, Y., Ma, W., Yan, W., Su, W., Wei, Z.. Small, 13(21), 1700388. (2017) 📅 (IF=15.6)
  20. Zhao, Y., Zou, W., Li, H., Lu, K., Yan, W., Wei, Z.. Chinese Journal of Polymer Science, 35(2), 261. (2017) 📅 (IF=3.8)
  21. Li, H., Zhao, Y., Zhu, X., Xia, B., Lu, K., Yuan, L., Zhang, J., Guo, X., Wei, Z.. Journal of Polymer Science Part A-Polymer Chemistry, 55(4), 699. (2017) 📅 (IF=2.8)
  22. Zhao, Y., Yuan, L., Zhang, J., Zhu, L., Lu, K., Yan, W., Wei, Z.. RSC Advances, 5(76), 61703. (2015) 📅 (IF=4.0)